Likelihood to Recommend AWS Document DB (with
MongoDB compatibility) is well suited when for all the workloads due to its huge feature offerings which will reduce our operational overhead and due to that we can focus more on our WorkLoad rather than optimising and fine tuning Databases. Its Offerings are Advanced Monitoring, DB cluster Upgrades, Migration Assistant, High Availability, Fault Tolerance, Data Durability, Security, Storage Auto Scaling, Backup Restore policies.AWS Document DB (with
MongoDB compatibility) some of the features that are there in some other services like
MongoDB Atlas that offers vast amount of features plus Supports Multi Cloud while Deploying Database clusters, Immediate support to latest Mongo DB versions, Mobile & Edge Sync like
Atlas Edge Sync, Freedom to choose Database deployment in Any top Public Cloud, Having more then 100 plus Monitoring and Telemetry metrics for index and schema recommendations, More Compatibility with
MongoDB queries.
Read full review Neo4J is great for creating network graphs or illustrating how things are related. It is also good for finding individuals or things that have greater influence than others in a system. It is not appropriate if you have standard data sets that can be analyzed using conventional methods or visualized using
Tableau , for example.
Read full review Pros Amazon DocumentDB (with MongoDB compatibility) provides Auto scaling of cluster as a by default functionality through this we can focus on more on our applications end Through AWS Document DB without much operation overhead we can configure for Database's high availability, Durability, Backup Restores policies, Advanced Monitoring, Security Parameters. Also they can provide us a Guide for Database Migration from any Supported Mongo DB vendor to AWS Document DB. Via AWS Document DB query Logging ( Profiling ) we can fine tune our database queries and hence improving our END to END Customer Experience and Product Enhancements. Read full review Mature Query language, I found Cypher QL to be mature in handling all sorts of problems we throw at it. Its expressive enough to be intuitive while providing rich features for various scenarios. Native support for REST API, that makes interacting with Neo4J intuitive and easy. Support for Procedures in Java, procedures are custom code that could be added to the Neo4J to write custom querying of data. The best part about the procedures is it could be invoked using the REST API. This allows us to overcome any shortcomings from their Cypher query language. Nice UI and interface for executing the Query and visualizing the response. UI access controlled by User credentials allows for neat access controls. Awesome free community edition for small-scale projects. Read full review Cons Give support for Latest Mongo DB versions available in market AWS Document DB is limited up to 32 shards per cluster and 2 shards per Document DB instance and all within single region Start supporting more numbers of Rich data types Should have access to MongoDB experts who throw light on Cutting edge mongoDB features and integration consulting. Read full review One of the hardest challenges that Neo4j had to solve was the horizontal scaling problem. I am not updated on recent developments, but at the time of my use, I couldn't find a viable solution. Neo4j does not play with other open source APIs like Blueprint. You have to use the native Neo4j API. There wasn't a visual tool to see your data. Of course, third party tools are always available, but I would have loved something which came with the Neo4j bundle. I love that Docker comes bundled with Kitematic, so it's not wrong to hope that Neo4j could also ship with some default visualization software. Read full review Usability [Based on] Query Language, Performance on small and large data sets, integration and deployment, analysis, API support, Interactive UI.
Read full review Alternatives Considered Neo4j is a graph store and has different use cases compared to another NoSQL Document store like
MongoDB .
MongoDB is a bad choice when joins are common as existing operators for joining two documents (similar to tables in a relational store) as Mongo 3.5 use SQL like join algorithms which are expensive.
MongoDB is a great choice when distributed schemaless rich document structures are important requirements. Cross document transaction support is not native to
MongoDB yet, whereas Neo4J is ACID complaint with all its operations.
Read full review Return on Investment Great Customer Experience as DB queries are fine tuned Less Operational Overhead to manage and take care of the Database Automatic applying of Small patches Read full review Positive: Less complex queries on graph structures, than in relational databases. Negative: maintenance is a huge deal, things doesn't work and break, requiring lengthy restore operations. Read full review ScreenShots Amazon DocumentDB (with MongoDB compatibility) Screenshots